#dataset
| ids | typology | context | type | Class | grave | pag | fig/tav | n | Taxonomic_index | weighted_taxonomic_index | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 908 | PAD_0002 | Cardarelli 2014 | Copezzato | A5 | Vasi a profilo continuo | NaN | 472 | 271 | 37985b | 5 | 1 |
| 909 | PAD_0003 | Cardarelli 2014 | Copezzato | A5 | Vasi a profilo continuo | NaN | 472 | 271 | 41380b | 5 | 1 |
| 910 | PAD_0004 | Cardarelli 2014 | Copezzato | A5 | Vasi a profilo continuo | NaN | 472 | 271 | 56163 | 5 | 1 |
| 911 | PAD_0005 | Cardarelli 2014 | Copezzato | A5 | Vasi a profilo continuo | NaN | 472 | 271 | 56165 | 5 | 1 |
| 914 | PAD_0008 | Cardarelli 2014 | Capriano del Colle | A5 | Vasi a profilo continuo | A | 472 | 271 | T.A | 5 | 1 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 634 | TRRGLL_0179 | Pacciarelli 1993 | Torre Galli | K2 | Pissidi | 110 | 303 | 77 | 4 | 66 | 54 |
| 651 | TRRGLL_0199 | Pacciarelli 1993 | Torre Galli | K2 | Pissidi | 119 | 310 | 84A | 2 | 66 | 54 |
| 757 | TRRGLL_0319 | Pacciarelli 1993 | Torre Galli | K2 | Pissidi | 183 | 349 | 123B | 1 | 66 | 54 |
| 678 | TRRGLL_0228 | Pacciarelli 1993 | Torre Galli | K4 | Pissidi | 133 | 320 | 94 | 4 | 68 | 55 |
| 814 | TRRGLL_0378 | Pacciarelli 1993 | Torre Galli | K4 | Pissidi | 217 | 373 | 147A | 4 | 68 | 55 |
1149 rows × 11 columns
for digital_type in pipeline_pots.AI_type.values:
selected_digit_type = no_noise.loc[no_noise.AI_type == digital_type]
plot_digital_types(data = selected_pots[selected_digit_type.index], info_selected = selected_digit_type, show_id=True, pot_title="ids", sub_title="type", )
Digital type: 73
Digital type: 68
Digital type: 11
Digital type: 26
Digital type: 63
Digital type: 34
Digital type: 84
Digital type: 62
Digital type: 35
Digital type: 29
Digital type: 12
Digital type: 93
Digital type: 75
Digital type: 86
Digital type: 5
Digital type: 87
Digital type: 74
Digital type: 92
Digital type: 10
Digital type: 99
Digital type: 82
Digital type: 70
Digital type: 52
Digital type: 55
Digital type: 57
Digital type: 61
Digital type: 49
Digital type: 27
Digital type: 56
Digital type: 37
Digital type: 36
Digital type: 66
Digital type: 80
Digital type: 83
Digital type: 69
Digital type: 38
Digital type: 102
Digital type: 25
Digital type: 72
Digital type: 103
Digital type: 101
Digital type: 51
Digital type: 100
Digital type: 91
Digital type: 98
Digital type: 88
Digital type: 81
Digital type: 33
Digital type: 77
Digital type: 94
Digital type: 78
Digital type: 40
Digital type: 43
Digital type: 44
Digital type: 41
Digital type: 23
Digital type: 67
Digital type: 59
Digital type: 4
Digital type: 90
Digital type: 96
Digital type: 95
Digital type: 76
Digital type: 97
Digital type: 3
Digital type: 60
Digital type: 71
Digital type: 32
Digital type: 20
Digital type: 39
Digital type: 28
Digital type: 0
Digital type: 14
Digital type: 89
Digital type: 58
Digital type: 85
Digital type: 21
Digital type: 79
Digital type: 22
Digital type: 42
Digital type: 50
Digital type: 64
Digital type: 6
Digital type: 1
Digital type: 65
Digital type: 8
Digital type: 13
Digital type: 7
Digital type: 53
Digital type: 17
Digital type: 9
Digital type: 45
Digital type: 31
Digital type: 18
Digital type: 24
Digital type: 47
Digital type: 48
Digital type: 15
Digital type: 54
Digital type: 19
Digital type: 16
Digital type: 30
Digital type: 46
Digital type: 2
pipeline_pots.mean()
C:\Users\larth\AppData\Local\Temp/ipykernel_6940/2181277370.py:1: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction.
AI_type 51.500000 Mean_pot_value 0.679524 N_pots 4.769231 Tassonomic_variability 14.488668 dtype: float64
pipeline_pots
| AI_type | Mean_pot_value | N_pots | Tassonomic_variability | correspondence | |
|---|---|---|---|---|---|
| 0 | 73 | 0.485340 | 10 | 50.140203 | NaN |
| 1 | 68 | 0.608384 | 5 | 24.489998 | NaN |
| 2 | 11 | 0.594954 | 6 | 2.426703 | ['A6'] |
| 3 | 26 | 0.486480 | 8 | 41.036379 | ['I16'] |
| 4 | 63 | 0.789930 | 3 | 2.160247 | NaN |
| 5 | 34 | 0.521257 | 5 | 25.487252 | NaN |
| 6 | 84 | 0.568523 | 8 | 34.115383 | NaN |
| 7 | 62 | 0.693291 | 3 | 35.863940 | NaN |
| 8 | 35 | 0.622356 | 5 | 28.322429 | NaN |
| 9 | 29 | 0.655536 | 6 | 21.090414 | ['A11'] |
| 10 | 12 | 0.606977 | 6 | 24.178158 | NaN |
| 11 | 93 | 0.628005 | 6 | 4.509250 | ['A16'] |
| 12 | 75 | 0.726473 | 4 | 19.723083 | NaN |
| 13 | 86 | 0.810663 | 3 | 24.097026 | NaN |
| 14 | 5 | 0.526529 | 5 | 16.473008 | ['A13'] |
| 15 | 87 | 0.607810 | 7 | 24.448196 | NaN |
| 16 | 74 | 0.671594 | 4 | 25.114737 | ['A13'] |
| 17 | 92 | 0.742343 | 3 | 1.247219 | NaN |
| 18 | 10 | 0.518019 | 7 | 16.461458 | NaN |
| 19 | 99 | 0.590600 | 7 | 17.307542 | NaN |
| 20 | 82 | 0.666185 | 6 | 21.587033 | NaN |
| 21 | 70 | 0.634974 | 6 | 19.379256 | ['E7'] |
| 22 | 52 | 0.720370 | 4 | 32.264532 | NaN |
| 23 | 55 | 0.686006 | 3 | 34.422215 | NaN |
| 24 | 57 | 0.665197 | 8 | 2.000000 | ['A24'] |
| 25 | 61 | 0.618022 | 6 | 23.893281 | NaN |
| 26 | 49 | 0.511090 | 7 | 33.289699 | NaN |
| 27 | 27 | 0.903798 | 3 | 24.984440 | ['A21'] |
| 28 | 56 | 0.800793 | 3 | 1.414214 | ['A24'] |
| 29 | 37 | 0.713657 | 5 | 22.471315 | ['A24'] |
| 30 | 36 | 0.505102 | 4 | 20.825165 | NaN |
| 31 | 66 | 0.600979 | 6 | 25.486925 | NaN |
| 32 | 80 | 0.650199 | 6 | 20.941718 | NaN |
| 33 | 83 | 0.718339 | 5 | 18.301912 | NaN |
| 34 | 69 | 0.692422 | 4 | 19.163768 | NaN |
| 35 | 38 | 0.700282 | 3 | 20.832667 | NaN |
| 36 | 102 | 0.748013 | 3 | 22.627417 | ['A26'] |
| 37 | 25 | 0.611917 | 6 | 18.743888 | NaN |
| 38 | 72 | 0.735388 | 4 | 22.387217 | ['E15'] |
| 39 | 103 | 0.738375 | 5 | 18.015549 | NaN |
| 40 | 101 | 0.728180 | 5 | 8.231646 | NaN |
| 41 | 51 | 0.566719 | 9 | 25.407785 | NaN |
| 42 | 100 | 0.683503 | 4 | 5.402546 | ['C8'] |
| 43 | 91 | 0.674654 | 4 | 8.042854 | NaN |
| 44 | 98 | 0.604506 | 5 | 21.872357 | NaN |
| 45 | 88 | 0.732746 | 4 | 17.014700 | ['C9'] |
| 46 | 81 | 0.806357 | 3 | 4.242641 | ['C6'] |
| 47 | 33 | 0.550698 | 9 | 18.156385 | NaN |
| 48 | 77 | 0.677066 | 3 | 22.171052 | NaN |
| 49 | 94 | 0.586193 | 4 | 24.233242 | NaN |
| 50 | 78 | 0.567453 | 6 | 25.230603 | ['C1'] |
| 51 | 40 | 0.641938 | 5 | 18.183509 | NaN |
| 52 | 43 | 0.573154 | 7 | 23.100490 | NaN |
| 53 | 44 | 0.630409 | 6 | 19.567547 | NaN |
| 54 | 41 | 0.698663 | 4 | 20.000000 | ['C4', 'E17'] |
| 55 | 23 | 0.633834 | 3 | 22.231109 | NaN |
| 56 | 67 | 0.614326 | 4 | 27.000000 | ['C5', 'F11'] |
| 57 | 59 | 0.597576 | 7 | 19.353848 | NaN |
| 58 | 4 | 0.808023 | 3 | 26.398653 | ['C6'] |
| 59 | 90 | 0.621471 | 4 | 3.112475 | NaN |
| 60 | 96 | 0.642158 | 3 | 18.624953 | NaN |
| 61 | 95 | 0.663726 | 4 | 7.088723 | ['C7'] |
| 62 | 76 | 0.753362 | 4 | 16.170962 | ['E17'] |
| 63 | 97 | 0.770698 | 3 | 15.839472 | NaN |
| 64 | 3 | 0.752593 | 4 | 20.820663 | NaN |
| 65 | 60 | 0.748334 | 4 | 9.246621 | ['E3'] |
| 66 | 71 | 0.811515 | 3 | 11.313708 | ['E7'] |
| 67 | 32 | 0.600710 | 3 | 2.494438 | NaN |
| 68 | 20 | 0.453305 | 7 | 1.277753 | NaN |
| 69 | 39 | 0.740107 | 4 | 4.690416 | ['E12'] |
| 70 | 28 | 0.787392 | 3 | 3.771236 | ['E3'] |
| 71 | 0 | 0.817432 | 3 | 14.839886 | NaN |
| 72 | 14 | 0.639674 | 6 | 23.900256 | NaN |
| 73 | 89 | 0.682601 | 4 | 0.000000 | ['E15'] |
| 74 | 58 | 0.797921 | 4 | 9.836158 | ['G2'] |
| 75 | 85 | 0.722972 | 3 | 1.414214 | ['F8'] |
| 76 | 21 | 0.672399 | 4 | 1.500000 | ['F11'] |
| 77 | 79 | 0.558541 | 5 | 0.748331 | NaN |
| 78 | 22 | 0.735293 | 3 | 11.145502 | NaN |
| 79 | 42 | 0.604754 | 5 | 5.621388 | NaN |
| 80 | 50 | 0.508626 | 4 | 7.632169 | NaN |
| 81 | 64 | 0.583859 | 6 | 6.633250 | ['L3'] |
| 82 | 6 | 0.531010 | 9 | 7.166451 | NaN |
| 83 | 1 | 0.734444 | 4 | 6.796139 | ['N3'] |
| 84 | 65 | 0.742748 | 4 | 2.277608 | ['I5'] |
| 85 | 8 | 0.741607 | 4 | 12.028612 | NaN |
| 86 | 13 | 0.787773 | 3 | 12.675436 | NaN |
| 87 | 7 | 0.684782 | 5 | 5.946427 | NaN |
| 88 | 53 | 0.811981 | 3 | 9.933110 | NaN |
| 89 | 17 | 0.700820 | 6 | 4.374802 | NaN |
| 90 | 9 | 0.812315 | 3 | 4.242641 | ['O9'] |
| 91 | 45 | 0.532238 | 11 | 4.028822 | NaN |
| 92 | 31 | 0.704690 | 9 | 2.997942 | NaN |
| 93 | 18 | 0.702741 | 4 | 1.299038 | ['O6'] |
| 94 | 24 | 0.793171 | 3 | 2.357023 | ['O4'] |
| 95 | 47 | 0.849786 | 3 | 2.357023 | ['O4'] |
| 96 | 48 | 0.777858 | 4 | 2.000000 | ['O5', 'O9'] |
| 97 | 15 | 0.798444 | 4 | 2.165064 | ['O6'] |
| 98 | 54 | 0.807193 | 4 | 1.500000 | ['O6', 'O9'] |
| 99 | 19 | 0.808974 | 3 | 2.357023 | ['O6'] |
| 100 | 16 | 0.849746 | 3 | 2.449490 | NaN |
| 101 | 30 | 0.849078 | 3 | 0.000000 | ['O6'] |
| 102 | 46 | 0.696284 | 5 | 1.166190 | ['O12'] |
| 103 | 2 | 0.831171 | 3 | 1.414214 | ['O12'] |
for digital_type in pipeline_pots.AI_type.values:
selected_digit_type = no_noise.loc[no_noise.AI_type == digital_type]
plot_digital_types(data = selected_pots[selected_digit_type.index], info_selected = selected_digit_type, show_id=True, pot_title="ids", sub_title="type", )
Digital type: 0
Digital type: 6
Digital type: 7
Digital type: 2
Digital type: 3
Digital type: 8
Digital type: 19
Digital type: 20
Digital type: 14
Digital type: 12
Digital type: 1
Digital type: 18
Digital type: 13
Digital type: 31
Digital type: 11
Digital type: 30
Digital type: 16
Digital type: 5
Digital type: 17
Digital type: 24
Digital type: 9
Digital type: 4
Digital type: 22
Digital type: 10
Digital type: 25
Digital type: 33
Digital type: 27
Digital type: 26
Digital type: 28
Digital type: 23
Digital type: 29
Digital type: 32
Digital type: 15
Digital type: 35
Digital type: 34
Digital type: 36
Digital type: 21
pipeline_pots
| AI_type | Mean_pot_value | N_pots | Tassonomic_variability | Correspondence | |
|---|---|---|---|---|---|
| 0 | 0 | 0.634835 | 5 | 6.740920 | NaN |
| 1 | 6 | 0.658898 | 4 | 7.449832 | NaN |
| 2 | 7 | 0.746334 | 3 | 3.299832 | ['8'] |
| 3 | 2 | 0.568266 | 8 | 4.728570 | NaN |
| 4 | 3 | 0.632567 | 4 | 0.866025 | ['7'] |
| 5 | 8 | 0.499502 | 7 | 3.251373 | NaN |
| 6 | 19 | 0.732170 | 4 | 1.785357 | ['13'] |
| 7 | 20 | 0.589643 | 4 | 1.089725 | ['11'] |
| 8 | 14 | 0.455669 | 5 | 23.215512 | NaN |
| 9 | 12 | 0.595627 | 8 | 5.612486 | NaN |
| 10 | 1 | 0.665467 | 4 | 7.361216 | ['39'] |
| 11 | 18 | 0.624761 | 5 | 1.743560 | NaN |
| 12 | 13 | 0.663299 | 5 | 3.059412 | NaN |
| 13 | 31 | 0.775303 | 5 | 2.939388 | ['37'] |
| 14 | 11 | 0.676464 | 3 | 3.299832 | NaN |
| 15 | 30 | 0.769901 | 3 | 2.494438 | NaN |
| 16 | 16 | 0.803873 | 3 | 2.357023 | ['37'] |
| 17 | 5 | 0.612095 | 7 | 2.050386 | NaN |
| 18 | 17 | 0.659420 | 3 | 0.942809 | ['40'] |
| 19 | 24 | 0.652675 | 3 | 10.842304 | ['44'] |
| 20 | 9 | 0.563237 | 5 | 7.949843 | NaN |
| 21 | 4 | 0.503236 | 7 | 5.678459 | NaN |
| 22 | 22 | 0.608299 | 4 | 7.500000 | NaN |
| 23 | 10 | 0.591072 | 6 | 6.693695 | NaN |
| 24 | 25 | 0.493288 | 7 | 7.342913 | NaN |
| 25 | 33 | 0.648729 | 4 | 7.154544 | NaN |
| 26 | 27 | 0.623472 | 5 | 7.445804 | NaN |
| 27 | 26 | 0.582084 | 5 | 9.744742 | NaN |
| 28 | 28 | 0.572744 | 3 | 2.357023 | ['57'] |
| 29 | 23 | 0.586778 | 5 | 4.841487 | NaN |
| 30 | 29 | 0.565970 | 4 | 2.947457 | NaN |
| 31 | 32 | 0.509599 | 6 | 4.856267 | NaN |
| 32 | 15 | 0.478703 | 6 | 4.932883 | ['71'] |
| 33 | 35 | 0.703754 | 3 | 1.885618 | ['66'] |
| 34 | 34 | 0.594473 | 4 | 1.224745 | ['63'] |
| 35 | 36 | 0.670121 | 3 | 0.471405 | ['63'] |
| 36 | 21 | 0.587405 | 4 | 1.500000 | ['64'] |
for digital_type in pipeline_pots.AI_type.values:
selected_digit_type = no_noise.loc[no_noise.AI_type == digital_type]
plot_digital_types(data = selected_pots[selected_digit_type.index], info_selected = selected_digit_type, show_id=True, pot_title="ids", sub_title="type", )
Digital type: 22
Digital type: 76
Digital type: 51
Digital type: 46
Digital type: 36
Digital type: 34
Digital type: 23
Digital type: 44
Digital type: 50
Digital type: 70
Digital type: 40
Digital type: 20
Digital type: 43
Digital type: 59
Digital type: 58
Digital type: 35
Digital type: 47
Digital type: 56
Digital type: 67
Digital type: 21
Digital type: 69
Digital type: 33
Digital type: 68
Digital type: 75
Digital type: 45
Digital type: 13
Digital type: 60
Digital type: 57
Digital type: 61
Digital type: 42
Digital type: 41
Digital type: 8
Digital type: 66
Digital type: 0
Digital type: 3
Digital type: 62
Digital type: 27
Digital type: 39
Digital type: 24
Digital type: 65
Digital type: 77
Digital type: 74
Digital type: 37
Digital type: 14
Digital type: 52
Digital type: 64
Digital type: 78
Digital type: 80
Digital type: 71
Digital type: 79
Digital type: 72
Digital type: 73
Digital type: 26
Digital type: 38
Digital type: 4
Digital type: 63
Digital type: 53
Digital type: 25
Digital type: 6
Digital type: 49
Digital type: 15
Digital type: 48
Digital type: 7
Digital type: 5
Digital type: 54
Digital type: 17
Digital type: 16
Digital type: 2
Digital type: 1
Digital type: 28
Digital type: 29
Digital type: 19
Digital type: 18
Digital type: 30
Digital type: 31
Digital type: 12
Digital type: 9
Digital type: 32
Digital type: 10
Digital type: 11
Digital type: 55
pipeline_pots
| AI_type | Mean_pot_value | N_pots | Tassonomic_variability | Correspondence | |
|---|---|---|---|---|---|
| 0 | 22 | 0.618766 | 10 | 5.491812 | NaN |
| 1 | 76 | 0.635474 | 5 | 5.713143 | ['Ab7'] |
| 2 | 51 | 0.671436 | 9 | 5.395471 | NaN |
| 3 | 46 | 0.633913 | 8 | 4.897385 | NaN |
| 4 | 36 | 0.632914 | 6 | 4.099458 | NaN |
| 5 | 34 | 0.588158 | 5 | 5.919459 | NaN |
| 6 | 23 | 0.711511 | 5 | 9.046546 | NaN |
| 7 | 44 | 0.649752 | 3 | 5.887841 | NaN |
| 8 | 50 | 0.652886 | 7 | 5.499536 | NaN |
| 9 | 70 | 0.780865 | 3 | 7.118052 | NaN |
| 10 | 40 | 0.732023 | 3 | 2.160247 | NaN |
| 11 | 20 | 0.690300 | 7 | 5.576920 | NaN |
| 12 | 43 | 0.728763 | 4 | 5.448624 | ['Ab3'] |
| 13 | 59 | 0.719413 | 7 | 5.154748 | NaN |
| 14 | 58 | 0.735544 | 4 | 7.648529 | NaN |
| 15 | 35 | 0.770060 | 3 | 6.342099 | NaN |
| 16 | 47 | 0.631722 | 7 | 6.249898 | NaN |
| 17 | 56 | 0.766230 | 4 | 3.561952 | NaN |
| 18 | 67 | 0.740480 | 4 | 6.576473 | NaN |
| 19 | 21 | 0.747476 | 4 | 4.716991 | ['Aa3'] |
| 20 | 69 | 0.737245 | 4 | 5.196152 | ['Aa3'] |
| 21 | 33 | 0.725741 | 4 | 5.356071 | ['Aa4'] |
| 22 | 68 | 0.830434 | 3 | 4.966555 | NaN |
| 23 | 75 | 0.560716 | 10 | 6.053098 | NaN |
| 24 | 45 | 0.675877 | 4 | 5.309190 | NaN |
| 25 | 13 | 0.668273 | 6 | 4.524624 | NaN |
| 26 | 60 | 0.574324 | 8 | 5.808130 | NaN |
| 27 | 57 | 0.748515 | 3 | 5.887841 | NaN |
| 28 | 61 | 0.663397 | 7 | 5.091008 | NaN |
| 29 | 42 | 0.618484 | 5 | 5.741080 | NaN |
| 30 | 41 | 0.807720 | 3 | 2.160247 | NaN |
| 31 | 8 | 0.723270 | 4 | 4.493050 | ['Ab3'] |
| 32 | 66 | 0.670312 | 3 | 0.942809 | ['Ab8'] |
| 33 | 0 | 0.690373 | 3 | 2.449490 | NaN |
| 34 | 3 | 0.665579 | 7 | 5.070926 | NaN |
| 35 | 62 | 0.473840 | 9 | 6.699917 | NaN |
| 36 | 27 | 0.469722 | 6 | 7.174414 | NaN |
| 37 | 39 | 0.594476 | 7 | 2.871393 | NaN |
| 38 | 24 | 0.629725 | 5 | 3.187475 | NaN |
| 39 | 65 | 0.627572 | 5 | 0.632456 | ['C2'] |
| 40 | 77 | 0.625282 | 4 | 1.500000 | ['C2'] |
| 41 | 74 | 0.530002 | 6 | 1.572330 | NaN |
| 42 | 37 | 0.633045 | 4 | 5.787918 | NaN |
| 43 | 14 | 0.589972 | 8 | 2.384848 | ['C2'] |
| 44 | 52 | 0.659325 | 6 | 3.337497 | NaN |
| 45 | 64 | 0.659005 | 4 | 0.000000 | ['C2'] |
| 46 | 78 | 0.621732 | 3 | 8.013877 | ['C2'] |
| 47 | 80 | 0.672914 | 4 | 1.479020 | NaN |
| 48 | 71 | 0.687569 | 3 | 0.000000 | ['C2'] |
| 49 | 79 | 0.731336 | 3 | 0.000000 | ['C2'] |
| 50 | 72 | 0.681448 | 3 | 3.741657 | NaN |
| 51 | 73 | 0.689286 | 4 | 1.500000 | ['C2', 'C5'] |
| 52 | 26 | 0.616178 | 4 | 6.869316 | NaN |
| 53 | 38 | 0.497654 | 7 | 14.202615 | NaN |
| 54 | 4 | 0.708484 | 3 | 2.160247 | NaN |
| 55 | 63 | 0.675607 | 3 | 6.683313 | NaN |
| 56 | 53 | 0.626034 | 4 | 1.920286 | ['C6'] |
| 57 | 25 | 0.802283 | 3 | 2.494438 | NaN |
| 58 | 6 | 0.449445 | 6 | 9.370462 | NaN |
| 59 | 49 | 0.740533 | 3 | 4.714045 | ['D4'] |
| 60 | 15 | 0.556257 | 4 | 2.449490 | ['E2'] |
| 61 | 48 | 0.675562 | 3 | 0.471405 | ['D4'] |
| 62 | 7 | 0.494803 | 6 | 7.542472 | ['G2'] |
| 63 | 5 | 0.577295 | 4 | 0.000000 | ['E2'] |
| 64 | 54 | 0.471586 | 6 | 7.909207 | ['J1'] |
| 65 | 17 | 0.474334 | 12 | 2.763854 | ['H5'] |
| 66 | 16 | 0.556280 | 5 | 3.720215 | NaN |
| 67 | 2 | 0.468532 | 9 | 4.771313 | NaN |
| 68 | 1 | 0.652996 | 3 | 4.784233 | NaN |
| 69 | 28 | 0.541868 | 5 | 9.987993 | NaN |
| 70 | 29 | 0.561741 | 8 | 1.854050 | NaN |
| 71 | 19 | 0.504932 | 6 | 2.808717 | ['H6'] |
| 72 | 18 | 0.647437 | 3 | 3.559026 | NaN |
| 73 | 30 | 0.610656 | 5 | 1.833030 | NaN |
| 74 | 31 | 0.631988 | 3 | 3.559026 | NaN |
| 75 | 12 | 0.579866 | 4 | 2.947457 | ['H3'] |
| 76 | 9 | 0.521097 | 6 | 1.674979 | ['H7'] |
| 77 | 32 | 0.700630 | 3 | 1.699673 | NaN |
| 78 | 10 | 0.452418 | 6 | 1.154701 | ['H7'] |
| 79 | 11 | 0.644878 | 3 | 0.471405 | ['H5'] |
| 80 | 55 | 0.729357 | 3 | 0.471405 | ['K2'] |